Zhun Wei
Papers
1
Total Citations
5
H-Index
1
About
Zhun Wei is a rising leader in computational imaging, with a primary focus on non-line-of-sight (NLOS) imaging—a transformative technique that enables seeing objects hidden around corners. His work addresses critical challenges in autonomous driving, robotic vision, medical imaging, and security monitoring by developing advanced reconstruction algorithms. Wei’s most notable contribution, "Non-line-of-sight reconstruction via structure sparsity regularization" (2023), introduces a novel sparsity-based framework that significantly improves reconstruction quality in low signal-to-noise conditions. This approach leverages the inherent structural sparsity of hidden scenes to recover clearer, more accurate images from indirect light measurements. Despite its recent publication, the paper has already garnered 5 citations, reflecting its immediate impact on the field. Wei’s research bridges the gap between theoretical imaging models and practical, real-world applications, offering robust solutions for challenging environments where direct line-of-sight is impossible. His work is essential reading for students and researchers interested in the frontiers of computational optics, inverse problems, and intelligent sensing systems.
Research Focus
Key Achievements
Top Papers
- 1Non-line-of-sight reconstruction via structure sparsity regularization5 citations · 2023